Montreal Exchange

Senior Data QA Analyst

Montreal Exchange$100K — $120K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in Software Quality Assurance focused on Data QA and Backend Automation
  • Proficient in Python programming for automation and scripting
  • Advanced SQL capabilities to handle complex queries and large datasets
  • Experience with AWS data pipelines and associated cloud technologies
  • Strong skills in API testing, particularly RESTful services
  • Familiar with performance testing tools for high-volume transactions
  • Availability for operational support during off-business hours

Responsibilities

  • Design and maintain Python-based automation scripts to simulate real-time trades
  • Validate ETL/ELT processes and data integrity within AWS
  • Execute advanced SQL queries to verify data accuracy across systems
  • Identify and analyze bottlenecks in data processing lifecycles
  • Conduct root cause analysis of issues affecting system performance

Benefits

  • Flexible hybrid work model (2-3 days in office)
  • Opportunity to work in a high-stakes environment with a focus on trade simulation
  • Engagement with advanced technologies in data and cloud infrastructure
  • Collaboration with experienced teams in Data & Analytics
  • Potential for professional development in performance optimization
Full Job Description
We are looking for a technical Senior Data QA to join our Datalinx cluster. This is a backend-heavy engineering role focused on high-volume trade simulation and data integrity. You will use Python to build automation frameworks that simulate thousands of real-time trades, ensuring our systems can handle market volatility. You will use complex SQL to deep-dive into our databases, validating that every byte of data flowing through our AWS pipelines is accurate, compliant, and timely.

If you enjoy breaking data pipelines, automating complex scenarios, and working in a high-stakes trading environment, this is the role for you.

This role reports to: Senior Manager, Data & Analytics & Enterprise Data Architect

Job Location: Hybrid (2-3 days in office) - based in Toronto, ON.

Key Accountabilities:

  • Build Simulation Frameworks: Design and maintain Python-based automation scripts (using Pytest/Requests) to simulate thousands of real-time trades and stress-test our trading platforms.
  • Data Pipeline Validation: Validate ETL/ELT processes within AWS. Ensure data flows correctly from ingestion to storage, identifying data loss or transformation errors.
  • Deep-Dive Analysis: Execute advanced SQL queries against MySQL/Snowflake/Hive databases to verify data accuracy, consistency, and completeness across the Datalinx ecosystem.
  • Performance Engineering: Identify bottlenecks in the data product lifecycle. Analyze how the system behaves under high load and work with developers to optimize performance.
  • Root Cause Analysis: Go beyond "reporting bugs." Trace issues back to the specific service, API endpoint, or database procedure causing the failure.


The Tech Stack:
  • Language: Python (Heavy scripting, Pytest, Pandas, Requests).
  • Database: SQL (MySQL, Snowflake, Hive, Athena).
  • Cloud: AWS (S3, Data Pipelines, EC2, EMR, Lambda functions, REST APIs).
  • Tools: GitHub, JIRA, Confluence

Must Haves:

  • 5+ years in Software Quality Assurance with a specific focus on Data QA and Backend Automation.
  • Python Expertise: You aren't just running scripts; you can write Python code from scratch to generate test data, mock APIs, and simulate user traffic.
  • Advanced SQL Skills: You can write complex joins and window functions to validate large datasets without relying on a GUI.
  • AWS & Cloud Data: Proven experience testing data pipelines and understanding how data moves through cloud infrastructure (AWS preferred).
  • API Testing: Strong experience testing RESTful APIs and integrating them into automation suites.
  • Performance Testing: Experience with load testing tools and strategies (simulating high-volume transactions).
  • Operational Support: Support releases during off-business hours, when planned. Also providing support in case of adhoc issues to ensure system reliability.

Nice to Haves:

  • Capital Markets Experience: Understanding of equity markets, trade lifecycles, and financial instruments.
  • Big Data Tech: Experience with Hadoop, Spark, or Hive.
  • Shell Scripting: Working knowledge of shell scripting in a Linux environment.


Salary Range: 100,000/year - 120,000/year CAD. Please note that the salary range included is a guideline only. The salary offered may vary based on factors, including, but not limited to, the successful candidate's relevant knowledge, skills, and experience.

The recruiting efforts for this role are intended to fill a vacant position.

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